{"id":"W2015129601","doi":"10.5539/res.v7n8p88","title":"Kinds of the Attribute in the Mari Language","year":2015,"lang":"en","type":"article","venue":"Review of European Studies","topic":"Discourse Analysis and Cultural Communication","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Homogeneous; Syntax; Subject (documents); Sentence; Linguistics; Object (grammar); Word (group theory); Computer science; Natural language processing; Artificial intelligence; Mathematics; Combinatorics; Philosophy; World Wide Web","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003247654,0.00003551161,0.000156713,0.000007236236,0.00007471138,0.000005627339,0.0004814033,0.000004186121,0.000007320351],"category_scores_gemma":[0.0006983451,0.00001489726,0.00008126285,0.0003197433,0.0001730233,0.00004176117,0.0001232202,0.00004521399,0.000008908151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001088048,"about_ca_system_score_gemma":0.0000158651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000143295,"about_ca_topic_score_gemma":0.0004577368,"domain_scores_codex":[0.9981073,0.001388395,0.0001873619,0.00004256957,0.0002193427,0.00005505444],"domain_scores_gemma":[0.9993896,0.0000568367,0.0001545945,0.000261017,0.000129343,0.00000861003],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000007479961,0.0003719485,0.02152999,0.002766085,0.0005379597,0.000007824748,0.4683486,0.000007802805,0.0001224172,0.1364948,0.2506359,0.1191692],"study_design_scores_gemma":[0.000127876,0.00002764939,0.03334798,0.00461588,0.0002238085,3.831449e-7,0.2406219,4.690267e-7,0.00001686139,0.0001863096,0.7207401,0.00009083202],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.02769419,0.6168784,3.688275e-7,0.0124308,0.00003526174,0.0001781774,0.000002309081,0.000003926531,0.3427765],"genre_scores_gemma":[0.8101176,0.1887148,0.000008952702,0.0005302527,0.00003114936,0.000001951864,0.00000117172,0.000001603594,0.0005925458],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7824234,"threshold_uncertainty_score":0.1125579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1999893493861507,"score_gpt":0.45415796130991,"score_spread":0.2541686119237593,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}